The Tibetan Plateau (TP) is one of the most complicated orographic regions worldwide, and due to the lack of quantitative observations, the different simulation biases are still existing via various climate models over the TP. In this study, a one-summer-month 6-km dynamical downscaling simulation is conducted to evaluate the improvement of the new gravity wave drag (GWD) scheme and cycled assimilation of observations from the Global Telecommunications System (GTS) by the three-dimensional variational data assimilation (3D-Var) method. The updated GWD scheme provides better simulation results for surface and vertical winds, temperature, and humidity. 3D-Var cycled assimilation of GTS observations with the GWD scheme further improves the wind forecasting at the upper atmosphere levels but enhances temperature cold bias over the TP, and the latter may be partly related to less surface sensible and latent heat flux after assimilation. Notably, it obviously performs better at the spatial distribution and temporal variation of daily precipitation, thus effectively reduces the precipitation wet bias, especially for the eastern TP. This benefits from the more accurate simulation of different precipitation categories by data assimilation, especially for the light rain (1–10 mm/day). The mechanism of less precipitation wet bias is that assimilation of GTS observation results in weaker monsoon flow water vapor transport from low-latitude oceans, weaker Tibetan High with more accurate circulation fields and less upward vertical velocity. This research may provide guidance for establishing a downscaling dataset of higher spatiotemporal resolution for the TP.

青藏高原（TP）是世界上最复杂的地形区之一，由于缺乏定量观测，通过TP上的各种气候模型仍然存在不同的模拟偏差。在这项研究中，进行了一个夏令时6公里的动态降尺度仿真，以评估新重力波阻力（GWD）方案的改进以及来自全球电信系统（GTS）的三维观测的周期同化变体数据同化（3D-Var）方法。更新的GWD方案针对表面和垂直风，温度和湿度提供了更好的模拟结果。利用GWD方案对GTS观测值进行3D-Var循环同化，进一步改善了高层大气的风向预报，但增强了TP的温度冷偏差，后者可能部分与同化后表面感热通量和潜热通量较低有关。值得注意的是，它在日降水量的空间分布和时间变化上显然表现更好，从而有效地降低了降水的湿偏度，特别是在东部TP。这得益于通过数据同化（特别是对于小雨（1-10毫米/天））对不同降水类别进行更精确的模拟。降水湿偏少的机理是，对GTS观测的同化导致来自低纬度海洋的季风流水汽输送较弱，藏高较弱，环流场更准确，垂直速度较小。这项研究可为建立更高时空分辨率的TP缩减规模数据集提供指导。